Ángel Miguel García-Vico

34 papers B 1C 1Misc 2Journal 21Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Energy-Efficient Eimeria Parasite Detection Using a Two-Stage Spiking Neural Network Architecture. CoRR Ángel Miguel García-Vico, Huseyin Seker, Muhammad Afzal
2026	J	`jnl`	Quantum-inspired Tensor Network for QUBO, QUDO and Tensor QUDO Problems with k-neighbors. CoRR Sergio Muñiz Subiñas, Alejandro Mata Ali, Jorge Martínez Martín, Miguel Franco Hernando, Javier Sedano, Ángel Miguel García-Vico
2025	J	`jnl`	Application of spiking neural networks and traditional artificial neural networks for solar radiation forecasting in photovoltaic systems in Arab countries. Neural Comput. Appl. Bahgat Ayasi, Iago Xabier Vázquez, Mohammed Saleh, Ángel Miguel García-Vico, Cristóbal J. Carmona
2025	J	`jnl`	Knapsack and Shortest Path Problems Generalizations From A Quantum-Inspired Tensor Network Perspective. CoRR Sergio Muñiz Subiñas, Jorge Martínez Martín, Alejandro Mata Ali, Javier Sedano, Ángel Miguel García-Vico
2025	—	`conf`	Knapsack and Shortest Path Problems Generalizations from a Quantum-Inspired Tensor Network Perspective. IQSOFT Sergio Muñiz Subiñas, Jorge Martínez Martín, Alejandro Mata Ali, Javier Sedano, Ángel Miguel García-Vico
2025	J	`jnl`	Optimization of the quantization of dense neural networks from an exact QUBO formulation. CoRR Sergio Muñiz Subiñas, Manuel L. González, Jorge Ruiz Gómez, Alejandro Mata Ali, Jorge Martínez Martín, Miguel Franco Hernando, Ángel Miguel García-Vico
2025	—	`conf`	Synchronising Fuzzy Labels in Federated Evolutionary Systems: A Preliminary Study. IDEAL (2) María Asunción Padilla-Rascón, Ángel Miguel García-Vico, Cristóbal J. Carmona
2025	J	`jnl`	Vacuum Spiker: A Spiking Neural Network-Based Model for Efficient Anomaly Detection in Time Series. CoRR Iago Xabier Vázquez, Javier Sedano, Muhammad Afzal, Ángel Miguel García-Vico
2024	—	`conf`	Advancing Computational Frontiers: Spiking Neural Networks in High-Energy Efficiency Computing Across Diverse Domains. CAEPIA Bahgat Ayasi, Ángel Miguel García-Vico, Cristóbal J. Carmona, Mohammed Saleh
2024	J	`jnl`	Combining traditional and spiking neural networks for energy-efficient detection of Eimeria parasites. Appl. Soft Comput. Iago Xabier Vázquez, Bahgat Ayasi, Huseyin Seker, Julián Luengo, Javier Sedano, Ángel Miguel García-Vico
2024	—	`conf`	Deep Learning Inference on Edge: A Preliminary Device Comparison. IDEAL (1) Manuel Luis González Hernandez, Jorge Ruiz, Lidia Andrés, Randy Lozada, Erik S. Skibinsky-Gitlin, Jorge Fernández, Javier Sedano, Ángel Miguel García-Vico
2024	—	`conf`	Low Consumption Models for Disease Diagnosis in Isolated Farms. IDEAL (1) Iago Xabier Vázquez, Ángel Miguel García-Vico, Huseyin Seker, Javier Sedano
2023	J	`jnl`	A Multiclustering Evolutionary Hyperrectangle-Based Algorithm. Int. J. Comput. Intell. Syst. Luis Alfonso Pérez Martos, Ángel Miguel García-Vico, Pedro González, Cristóbal José Carmona
2023	J	`jnl`	A distributed evolutionary fuzzy system-based method for the fusion of descriptive emerging patterns in data streams. Inf. Fusion Ángel Miguel García-Vico, Cristóbal J. Carmona, Pedro González, María José del Jesus
2023	J	`jnl`	Clustering: an R library to facilitate the analysis and comparison of cluster algorithms. Prog. Artif. Intell. Luis Alfonso Pérez Martos, Ángel Miguel García-Vico, Pedro González, Cristóbal J. Carmona
2023	—	`conf`	FAS-CT: FPGA-Based Acceleration System with Continuous Training. FedCSIS (Communication Papers) Manuel Luis González Hernandez, Jorge Ruiz, Randy Lozada, Erik Sebastian Skibinsky Gitlin, Ángel Miguel García-Vico, Javier Sedano, José Ramón Villar
2023	J	`jnl`	TSFEDL: A python library for time series spatio-temporal feature extraction and prediction using deep learning. Neurocomputing Ignacio Aguilera-Martos, Ángel Miguel García-Vico, Julián Luengo, Sergio Damas, Francisco J. Melero, José Javier Valle-Alonso, Francisco Herrera
2022	Misc	`conf`	A Case of Study with the Clustering R Library to Measure the Quality of Cluster Algorithms. HAIS Luis Alfonso Pérez Martos, Ángel Miguel García-Vico, Pedro González, Cristóbal José Carmona
2022	C	`conf`	Performance/Resources Comparison of Hardware Implementations on Fully Connected Network Inference. IDEAL Randy Lozada, Jorge Ruiz, Manuel Luis González Hernandez, Javier Sedano, José R. Villar, Ángel Miguel García-Vico, Erik S. Skibinsky-Gitlin
2022	J	`jnl`	TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study). CoRR Ignacio Aguilera-Martos, Ángel Miguel García-Vico, Julián Luengo, Sergio Damas, Francisco J. Melero, José Javier Valle-Alonso, Francisco Herrera
2021	—	`conf`	A Comparison of Techniques for Virtual Concept Drift Detection. SOCO Manuel Luis González Hernandez, Javier Sedano, Ángel Miguel García-Vico, José Ramón Villar
2021	Misc	`conf`	A Preliminary Analysis on Software Frameworks for the Development of Spiking Neural Networks. HAIS Ángel Miguel García-Vico, Francisco Herrera
2021	J	`jnl`	A cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams. Expert Syst. Appl. Ángel Miguel García-Vico, Cristóbal J. Carmona, Pedro González, María José del Jesus
2020	—	`conf`	A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns. SOCO Ángel Miguel García-Vico, Cristóbal José Carmona, Pedro González, María José del Jesus
2020	J	`jnl`	E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments. Neurocomputing Ángel Miguel García-Vico, Francisco Charte, Pedro González, David A. Elizondo, Cristóbal José Carmona
2020	J	`jnl`	FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams. IEEE Trans. Fuzzy Syst. Ángel Miguel García-Vico, Cristóbal J. Carmona, Pedro González, Huseyin Seker, María José del Jesus
2019	J	`jnl`	A Big Data Approach for the Extraction of Fuzzy Emerging Patterns. Cogn. Comput. Ángel Miguel García-Vico, Pedro González, Cristóbal José Carmona, María José del Jesus
2019	J	`jnl`	Subgroup Discovery on Multiple Instance Data. Int. J. Comput. Intell. Syst. José María Luna, Cristóbal J. Carmona, Ángel Miguel García-Vico, María José del Jesus, Sebastián Ventura
2018	J	`jnl`	An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects. WIREs Data Mining Knowl. Discov. Ángel Miguel García-Vico, Cristóbal J. Carmona, Diana Martín, Milton García-Borroto, María José del Jesus
2018	J	`jnl`	Improvement of subgroup descriptions in noisy data by detecting exceptions. Prog. Artif. Intell. Pedro González García, Ángel Miguel García-Vico, Cristóbal J. Carmona, María José del Jesus
2018	J	`jnl`	MOEA-EFEP: Multi-Objective Evolutionary Algorithm for Extracting Fuzzy Emerging Patterns. IEEE Trans. Fuzzy Syst. Ángel Miguel García-Vico, Cristóbal J. Carmona, Pedro González, María José del Jesus
2017	B	`conf`	A first approach to handle fuzzy emerging patterns mining on big data problems: The EvAEFP-spark algorithm. FUZZ-IEEE Ángel Miguel García-Vico, Pedro González, María José del Jesus, Cristóbal J. Carmona
2016	—	`conf`	Analysing Concentrating Photovoltaics Technology Through the Use of Emerging Pattern Mining. SOCO-CISIS-ICEUTE Ángel Miguel García-Vico, J. Montes, Jorge Aguilera, Cristóbal J. Carmona, María José del Jesus
2016	J	`jnl`	The influence of noise on the evolutionary fuzzy systems for subgroup discovery. Soft Comput. Julián Luengo, Ángel Miguel García-Vico, M. Dolores Pérez-Godoy, Cristóbal J. Carmona